Triple

T37205334
Position Surface form Disambiguated ID Type / Status
Subject Dr. Leslie Thompkins E922153 entity
Predicate creator P184 FINISHED
Object Dick Giordano
Dick Giordano was an influential American comic book artist, inker, and editor best known for his work at DC Comics and his role in shaping the modern look of iconic characters like Batman.
E1462163 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Dick Giordano | Statement: [Dr. Leslie Thompkins, creator, Dick Giordano]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dick Giordano
Triple: [Dr. Leslie Thompkins, creator, Dick Giordano]
Generated description
Dick Giordano was an influential American comic book artist, inker, and editor best known for his work at DC Comics and his role in shaping the modern look of iconic characters like Batman.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f76ea4849481909b4a3073efb0114c completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb366d07b081908bd0d06fcea6c4f9 completed May 6, 2026, 12:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043b6ef788190bb286997844c07be completed June 27, 2026, 9:42 p.m.
NEDg Description generation batch_6a404499f25c81909aa809e44d76ce0d completed June 27, 2026, 9:46 p.m.
NED2 Entity disambiguation (via description) batch_6a404599f71c81909f3ba82c2ea8885c completed June 27, 2026, 9:50 p.m.
Created at: May 3, 2026, 4:15 p.m.